asimov_injury_val

• Description:

Situations generated from real hospital injury reports (validation set).

• Homepage: https://asimov-benchmark.github.io/

• Source code: tfds.robotics.asimov.AsimovInjuryVal

• Versions:

  • 0.1.0 (default): Initial release.

• Download size: Unknown size

• Dataset size: 5.20 MiB

• Auto-cached (documentation): Yes

• Splits:

Split	Examples
'val'	304

• Feature structure:

FeaturesDict({
    'context': Text(shape=(), dtype=string),
    'context_input_data': FeaturesDict({
        'Age': int32,
        'Alcohol': float32,
        'Body_Part': float32,
        'Body_Part_2': float32,
        'CPSC_Case_Number': Text(shape=(), dtype=string),
        'Diagnosis': float32,
        'Diagnosis_2': float32,
        'Disposition': float32,
        'Drug': float32,
        'Fire_Involvement': float32,
        'Gender': float32,
        'Hispanic': float32,
        'Location': float32,
        'Narrative_1': Text(shape=(), dtype=string),
        'Other_Diagnosis': Text(shape=(), dtype=string),
        'Other_Diagnosis_2': Text(shape=(), dtype=string),
        'Other_Race': Text(shape=(), dtype=string),
        'PSU': float32,
        'Product_1': float32,
        'Product_2': float32,
        'Product_3': float32,
        'Race': float32,
        'Stratum': Text(shape=(), dtype=string),
        'Treatment_Date': Text(shape=(), dtype=string),
        'Weight': float32,
    }),
    'instruction': Text(shape=(), dtype=string),
    'prompt_with_constitution': Text(shape=(), dtype=string),
    'prompt_with_constitution_chain_of_thought': Text(shape=(), dtype=string),
    'prompt_with_constitution_chain_of_thought_antijailbreak': Text(shape=(), dtype=string),
    'prompt_with_constitution_chain_of_thought_antijailbreak_adversary': Text(shape=(), dtype=string),
    'prompt_with_constitution_chain_of_thought_antijailbreak_adversary_parts': Sequence(Text(shape=(), dtype=string)),
    'prompt_with_constitution_chain_of_thought_antijailbreak_parts': Sequence(Text(shape=(), dtype=string)),
    'prompt_with_constitution_chain_of_thought_parts': Sequence(Text(shape=(), dtype=string)),
    'prompt_with_constitution_parts': Sequence(Text(shape=(), dtype=string)),
    'prompt_without_constitution': Text(shape=(), dtype=string),
    'prompt_without_constitution_parts': Sequence(Text(shape=(), dtype=string)),
    'undesirable_groundtruth_answer': bool,
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
context	Text		string
context_input_data	FeaturesDict
context_input_data/Age	Tensor		int32
context_input_data/Alcohol	Tensor		float32
context_input_data/Body_Part	Tensor		float32
context_input_data/Body_Part_2	Tensor		float32
context_input_data/CPSC_Case_Number	Text		string
context_input_data/Diagnosis	Tensor		float32
context_input_data/Diagnosis_2	Tensor		float32
context_input_data/Disposition	Tensor		float32
context_input_data/Drug	Tensor		float32
context_input_data/Fire_Involvement	Tensor		float32
context_input_data/Gender	Tensor		float32
context_input_data/Hispanic	Tensor		float32
context_input_data/Location	Tensor		float32
context_input_data/Narrative_1	Text		string
context_input_data/Other_Diagnosis	Text		string
context_input_data/Other_Diagnosis_2	Text		string
context_input_data/Other_Race	Text		string
context_input_data/PSU	Tensor		float32
context_input_data/Product_1	Tensor		float32
context_input_data/Product_2	Tensor		float32
context_input_data/Product_3	Tensor		float32
context_input_data/Race	Tensor		float32
context_input_data/Stratum	Text		string
context_input_data/Treatment_Date	Text		string
context_input_data/Weight	Tensor		float32
instruction	Text		string
prompt_with_constitution	Text		string
prompt_with_constitution_chain_of_thought	Text		string
prompt_with_constitution_chain_of_thought_antijailbreak	Text		string
prompt_with_constitution_chain_of_thought_antijailbreak_adversary	Text		string
prompt_with_constitution_chain_of_thought_antijailbreak_adversary_parts	Sequence(Text)	(None,)	string
prompt_with_constitution_chain_of_thought_antijailbreak_parts	Sequence(Text)	(None,)	string
prompt_with_constitution_chain_of_thought_parts	Sequence(Text)	(None,)	string
prompt_with_constitution_parts	Sequence(Text)	(None,)	string
prompt_without_constitution	Text		string
prompt_without_constitution_parts	Sequence(Text)	(None,)	string
undesirable_groundtruth_answer	Tensor		bool

• Supervised keys (See as_supervised doc): None

• Figure (tfds.show_examples): Not supported.

• Examples (tfds.as_dataframe):

• Citation:

@article{sermanet2025asimov,
  author    = {Pierre Sermanet and Anirudha Majumdar and Alex Irpan and Dmitry Kalashnikov and Vikas Sindhwani},
  title     = {Generating Robot Constitutions & Benchmarks for Semantic Safety},
  journal   = {arXiv preprint arXiv:2503.08663},
  url       = {https://arxiv.org/abs/2503.08663},
  year      = {2025},
}